{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1de1cc57-e5ec-42eb-af3a-e9f95160b810",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import the library\n",
    "import webmo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "decf682e-646d-412e-9e68-ccb8f58c9708",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter WebMO password for user smith: ········\n"
     ]
    }
   ],
   "source": [
    "# start a REST session\n",
    "URL = \"https://server.university.edu/~webmo/cgi-bin/webmo/rest.cgi\"\n",
    "Username = \"smith\"\n",
    "rest = webmo.WebMOREST(URL, username=Username)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fbe34985-da61-4cdf-92fd-1b4750880366",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Set a job ID\n",
    "job_number = 72"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c9e2c498-4f44-4ca5-b6c7-c237ceccc4e8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Energy: -113.866331244 Hartree\n"
     ]
    }
   ],
   "source": [
    "# Get its energy\n",
    "results = rest.get_job_results(job_number)\n",
    "energy = results['properties']['rhf_energy']['value']\n",
    "units = results['properties']['rhf_energy']['units']\n",
    "print(\"Energy: {} {}\".format(energy, units))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "39495f3b-1036-4e3f-b23c-c6c03343ddd0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<webmo.webmo_rest.EmbeddedImage object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display its geometry\n",
    "await rest.display_job_property(job_number, \"geometry\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb5aeee6-966e-45e7-8862-dd4f8b73a9e7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}